Rough set and granular computing merged method for mining online data of distributed heterogeneous mass urban safety data flows

Abstract

Provided is a rough set and granular computing merged method for mining online data of distributed heterogeneous mass urban safety data flows. A rough set theory and a data mining technology are introduced to achieve analysis and mining of the urban safety data flows, a distributed heterogeneous mass data flow concept formalized description model is firstly established, coupling analysis is performed on the concept model, node association is mined and found by adopting a rough set mass data partitioning method based on attribute reduction according to concept lattice based node pair association rules, finally key event information influencing urban safety is obtained through flexible granular computing, and urban digital management is achieved. The rough set and granular computing merged method for mining the online data of the distributed heterogeneous mass urban safety data flows is high in mining accuracy, good in timeliness and good in data validity.

Description

technical field [0001] The invention relates to knowledge in the technical field of data mining, in particular to an online data mining method for distributing heterogeneous massive urban security data streams. Background technique [0002] The state of urban public security is an important symbol of a country's competitiveness and image. As cities gather populations and accumulate wealth, the importance of cities has become increasingly apparent, yet they also face increasing security challenges. The increase in the frequency and intensity of natural disasters, the growth of various social accidents and the threat of terrorism have put forward more severe requirements on the ability of cities to prevent disasters and deal with emergencies. Statistics show that the annual economic loss caused by urban public safety issues in my country reaches 650 billion yuan, accounting for about 6% of the total GDP. The White Paper "China's Disaster Reduction Actions" published by the S...

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Problems solved by technology

[0004] In order to overcome the deficiencies of the existing urban public safety data that cannot be accurately and timely mined and the data validity is poor, the present invention provides a fusion rough set with high mining accuracy, good timeliness and good data validity Online Data Mining Method for Distributed Heterogeneous Massive Urban Security Data Streams with Granular Computing

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